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Alation buys Numbers Station to boost AI data workflow tools

May 21, 2025•by Duncan Riley•Original Link•2 minutes
AI
EnterpriseData
Acquisition

Alation acquires Numbers Station to enhance AI agent capabilities for enterprise data workflows

Data intelligence company Alation Inc. announced its acquisition of Numbers Station Inc., a startup specializing in AI agents for data workflows. The deal amount remains undisclosed.

  • Key Details:

    • Numbers Station, spun out of Stanford University's AI labs in 2021, focuses on automating complex data workflows for enterprises.
    • Its platform uses large language models to enable natural language interactions with structured data, eliminating the need for SQL or custom scripts.
    • The multi-agent architecture assigns tasks like data cleaning, transformation, and analysis to different AI agents, streamlining end-to-end workflows.
  • Integration Plans:

    • Numbers Station's AI agents will combine with Alation's metadata foundation to create intelligent applications for real-time decision-making.
    • The merger aims to maintain governance and compliance while delivering scalable business outcomes.
  • Leadership Insight:

    "Numbers Station has proven the impact AI agents can have in the enterprise," said Alation CEO Satyen Sangani. "Together, we're laying the foundation for the next decade of enterprise data intelligence."

  • Post-Acquisition:

    • Numbers Station's team will join Alation, with existing customers receiving continued support.
    • The startup had raised $12.5M from investors including Madrona Venture Group and Norwest Venture Partners.

Numbers Station Team

For more context, watch Sangani's Dreamforce 2024 interview about AI model compliance.

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Lenovo earns Frost Sullivan's 2025 Asia-Pacific AI Services Customer Value Leadership Recognition for its value-driven innovation and real-world AI impact.

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Baidu Wenku GenFlow 2.0 Revolutionizes AI Agents with Multi-Agent Architecture

Baidu Wenku's GenFlow 2.0 introduces a multi-agent system for parallel task processing, integrating with Cangzhou OS to enhance efficiency and redefine AI workflows.

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About the Author

Dr. Sarah Chen

Dr. Sarah Chen

AI Research Expert

A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.

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Machine Learning
Natural Language Processing
Deep Learning
AI Ethics
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